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Wavelet LSTM for Fault Forecasting in Electrical Power Grids

2022-10-30Journal article Open access
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dc.contributor.authorBranco, Nathielle
dc.contributor.authorSantos Matos Cavalca, Mariana
dc.contributor.authorStefenon, Stéfano Frizzo
dc.contributor.authorLEITHARDT, VALDERI
dc.date.accessioned2023-02-01T18:09:26ZPT
dc.date.available2023-02-01T18:09:26ZPT
dc.date.issued2022-10-30PT
dc.date.updated2022-11-03T15:10:51Z
dc.description.abstractAn electric power distribution utility is responsible for providing energy to consumers in a continuous and stable way. Failures in the electrical power system reduce the reliability indexes of the grid, directly harming its performance. For this reason, there is a need for failure prediction to reestablish power in the shortest possible time. Considering an evaluation of the number of failures over time, this paper proposes performing failure prediction during the first year of the pandemic in Brazil (2020) to verify the feasibility of using time series forecasting models for fault prediction. The long short-term memory (LSTM) model will be evaluated to obtain a forecast result that an electric power utility can use to organize maintenance teams. The wavelet transform has shown itself to be promising in improving the predictive ability of LSTM, making the wavelet LSTM model suitable for the study at hand. The assessments show that the proposed approach has better results regarding the error in prediction and has robustness when statistical analysis is performed.pt_PT
dc.description.sponsorshipGRANT_NUMBER: 32020
dc.description.versionN/Apt_PT
dc.identifier.doi10.3390/s22218323pt_PT
dc.identifier.slugcv-prod-3069993PT
dc.identifier.urihttp://hdl.handle.net/10400.26/43551PT
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectelectrical power grids;pt_PT
dc.subjectfault forecasting;pt_PT
dc.subjectlong short-term memory;pt_PT
dc.subjecttime series forecasting;pt_PT
dc.subjectwavelet transformpt_PT
dc.titleWavelet LSTM for Fault Forecasting in Electrical Power Gridspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titleSensorspt_PT
person.familyNameBranco
person.familyNameSantos Matos Cavalca
person.familyNameStefenon
person.familyNameREIS QUIETINHO LEITHARDT
person.givenNameNathielle
person.givenNameMariana
person.givenNameStefano Frizzo
person.givenNameVALDERI
person.identifier916543
person.identifierJsOq45sAAAAJ&hl=pt-PT
person.identifier.ciencia-id4019-BB36-7F74
person.identifier.ciencia-id0614-5834-E7F3
person.identifier.orcid0000-0001-7565-3274
person.identifier.orcid0000-0001-5728-2158
person.identifier.orcid0000-0002-3723-616X
person.identifier.orcid0000-0003-0446-9271
person.identifier.ridAAD-7639-2019
person.identifier.scopus-author-id36545649600
person.identifier.scopus-author-id57194147390
person.identifier.scopus-author-id35303109600
rcaap.cv.cienciaid0614-5834-E7F3 | Valderi Reis Quietinho Leithardt
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublicationab15f7c6-e882-406e-813d-2629e9cec5c8
relation.isAuthorOfPublication.latestForDiscovery4d5ebdfb-3a32-4508-8692-156f7fa846aa

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